{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# ***Introduction to Radar Using Python and MATLAB***\n",
    "## Andy Harrison - Copyright (C) 2019 Artech House\n",
    "<br/>\n",
    "\n",
    "# Bistatic Radar Range Equation\n",
    "***"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The power at the receiving radar for a bistatic configuration is given by (Equation 4.60)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " \\begin{equation}\n",
    "     P_{radar} = \\frac{P_t\\, G_t(\\theta, \\phi)\\, G_r(\\theta, \\phi)\\, \\sigma(\\theta, \\phi)\\, \\lambda^2}{(4\\pi)^3\\, r_t^2\\, r_r^2} \\hspace{0.5in} \\text{(W)}\n",
    " \\end{equation}\n",
    " ***"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Begin by getting the library path"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import lib_path"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Set the minimum and maximum range product (m)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "range_product_min = 1e6\n",
    "\n",
    "range_product_max = 1e7"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Import the `linspace` routine from `scipy`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from numpy import linspace"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Set up the range product array"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "range_product = linspace(range_product_min, range_product_max, 2000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Set up the transmit antenna gain (dB), receive antenna gain (dB),  bistatic target RCS (dBsm), peak transmit power (W), and the operating frequency (Hz)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "transmit_antenna_gain = 25.0\n",
    "\n",
    "receive_antenna_gain = 30.0\n",
    "\n",
    "bistatic_target_rcs = -10.0\n",
    "\n",
    "peak_power = 50e3\n",
    "\n",
    "frequency = 1e9"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Set up the input args"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "kwargs = {'transmit_target_range': 1.0,\n",
    "\n",
    "          'receive_target_range': range_product,\n",
    "\n",
    "          'peak_power': peak_power,\n",
    "\n",
    "          'transmit_antenna_gain': 10 ** (transmit_antenna_gain / 10.0),\n",
    "\n",
    "          'receive_antenna_gain': 10 ** (receive_antenna_gain / 10.0),\n",
    "\n",
    "          'frequency': frequency,\n",
    "          \n",
    "          'bistatic_target_rcs': 10 ** (bistatic_target_rcs / 10.0)}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Import the `power_at_radar` routine from `bistatic_radar_range`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "from Libs.radar_range.bistatic_radar_range import power_at_radar"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Calculate the power at the receiving radar"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "power_at_radar = power_at_radar(**kwargs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Import the `matplotlib` routines and `log10` from `scipy` for displaying the results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "\n",
    "from numpy import log10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Set the figure size\n",
    "\n",
    "plt.rcParams[\"figure.figsize\"] = (15, 10)\n",
    "\n",
    "\n",
    "# Display the results\n",
    "\n",
    "plt.plot(range_product / 1.0e6, power_at_radar, '')\n",
    "\n",
    "\n",
    "# Set the plot title and labels\n",
    "\n",
    "plt.title('Bistatic Power at the Receiver', size=14)\n",
    "\n",
    "plt.xlabel('Range Product (km$^2$)', size=12)\n",
    "\n",
    "plt.ylabel('Power at Receiver (W)', size=12)\n",
    "\n",
    "\n",
    "# Set the tick label size\n",
    "\n",
    "plt.tick_params(labelsize=12)\n",
    "\n",
    "\n",
    "# Turn on the grid\n",
    "\n",
    "plt.grid(linestyle=':', linewidth=0.5)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
